Rewriting Natural Language Queries Using Patterns

In this paper, a method based on pre-defined patterns, which rewrites natural language queries into a multi-layer, flexible, scalable and object-oriented query language, is presented. The method has been conceived to assist physicians in their search for clinical information in an Electronic Health Records system. Indeed, the query language of the system being difficult to handle for physicians, this method allows querying using natural language vs. using dedicated object-oriented query language. The information extraction method that has been developed can be seen as a named entity recognition system based on regular expressions that tags pieces of the query. The patterns are constructed recursively from the initial natural language query and from atomic patterns that correspond to the entities, the relationships and the constraints of the underlying model representing Electronic Health Records. Further evaluation is needed, but the preliminary results obtained by testing a set of natural language queries are very encouraging.